How much time should I budget?

About 3 hours total, a working session and a review call. We do the heavy lifting.

What if I only want the roadmap, not the build?

That's the Campaign Repositioning Sprint. Ship it yourself, or upgrade to Done-For-You later.

Do you interview my customers?

Optional. We can mine your call recordings, reviews, and won/lost notes instead.

B2B teams spending $20K+/mo on ads whose demos aren't converting.

Book a 30-minute call. We'll tell you straight if it's a fit.

Where Parallel's ads lose the buyer

Parallel is running 16 live ads on LinkedIn and Google. Their average fit to their own ideal buyer is 7.3 out of 10, and 3 ads need fixing. Each ad below is one of Parallel’s real live creatives, read straight from the ad libraries.

Parallel’s live ads, scored against their buyer

The outside world is the new infrastructure for AI agents, scored 6/10 against Parallel’s ideal buyer. Thought-leadership framing resonates with the ICP but offers no specific product proof or CTA to act on.
Up to 5,000 free monthly searches, scored 9/10 against Parallel’s ideal buyer. Benchmark chart beats every named rival on accuracy and latency, free tier lowers friction, price is explicit.
Ultra fast agents need ultra fast web search. Parallel Search Turbo delivers 200, scored 8/10 against Parallel’s ideal buyer. Concrete latency and price specs land squarely on the AI engineer's core build criteria.
Get started for free, scored 7/10 against Parallel’s ideal buyer. Finance use-case query on creative shows real-world agent grounding, but free CTA undersells the API's production value.
Web Scraping API No Complex Scraping Code, scored 8/10 against Parallel’s ideal buyer. Sharp price anchor, token-waste pain, and pipeline framing hit the AI engineer's exact build decision.
Free Tier for Parallel, scored 6/10 against Parallel’s ideal buyer. Free credits lower friction but 'What's trending now?' query feels consumer, not developer-grade agent use case.
Parallel Search API Parallel AI Web Search, scored 7/10 against Parallel’s ideal buyer. Hallucination reduction and verifiable citations address core ICP pain, but headline is brand-generic rather than outcome-led.
Extract API for AI Agents, scored 8/10 against Parallel’s ideal buyer. One-line value prop eliminates infra pain precisely for the AI engineer building data pipelines.
LLM Search API One API for the Whole Web, scored 8/10 against Parallel’s ideal buyer. SDK and MCP Server callouts signal developer-ready tooling, and free trial lowers adoption friction for the right buyer.
Parallel Extract API, scored 7/10 against Parallel’s ideal buyer. Plain-English objective framing and price anchor speak directly to LLM builders.
Works With Any Public URL - Turn URLs into Context, scored 7/10 against Parallel’s ideal buyer. Puppeteer and Playwright callout lands a sharp competitive hook for the right builder.
Web Scraping API - Automated Web Scraping For AI, scored 8/10 against Parallel’s ideal buyer. Context-window token waste is a precise, felt pain for AI engineers building agents.
Parallel Search API - Highest Accuracy Search API, scored 7/10 against Parallel’s ideal buyer. Real-time context plus token cost reduction hits two core ICP motivators cleanly.
Extract API: Start Free - Works With Any Public URL, scored 7/10 against Parallel’s ideal buyer. Free entry point and no-infra promise reduce friction for engineers evaluating alternatives.
Parallel Search API - Highest Accuracy Search API, scored 6/10 against Parallel’s ideal buyer. Truncated 'Unmatched' claim loses the proof that would justify the superlative.
Web Scraping API - Web Scraping Built For LLMs, scored 8/10 against Parallel’s ideal buyer. Stacks price, pipeline scale, and token-waste pain into one tight message for AI engineers.

See Parallel’s full live-ad board on AdRoast. Every creative scored against their ICP, with the exact fix for each.

Learn the method behind these scores: the AdRoast guides cover how to audit your ads against your ICP and why clicks do not turn into pipeline.